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LIGHT SCATTERING PROPERTIES VARY ACROSS DIFFERENT REGIONS OF 

THE ADULT MOUSE BRAIN 
by 

SAIF I. AL-JUBOORI 
B.S., Nahrain University, 2008 



A thesis submitted to the 
Faculty of the Graduate School of the 
University of Colorado in partial fulfillment 
of the requirements for the degree of 
Master of Science 
Electrical Engineering 
2013 



This thesis for the Master of Science degree by 
Saif I. Al-Juboori 
has been approved for the 
Electrical Engineering Program 
by 



Tim Lei, Chair 
Achim Klug 
Yiming Deng 



Al-Juboori, Saif, I. (M.S., Electrical Engineering) 

Light Scattering Properties Vary across Different Regions of the Adult Mouse Brain 
Thesis directed by Assistant Professor Tim Lei. 

ABSTRACT 

Recently developed optogenetic tools provide powerful approaches to optically 
excite or inhibit neural activity. In a typical in- vivo experiment, light is delivered to deep 
nuclei via an implanted optical fiber. Light intensity attenuates with increasing distance 
from the fiber tip, determining the volume of tissue in which optogenetic proteins can 
successfully be activated. However, whether and how this volume of effective light 
intensity varies as a function of brain region or wavelength has not been systematically 
studied. 

The goal of this study was to measure and compare how light scatters in different 
areas of the mouse brain. We delivered different wavelengths of light via optical fibers to 
acute slices of mouse brainstem, midbrain and forebrain tissue. We measured light 
intensity as a function of distance from the fiber tip, and used the data to model the 
spread of light in specific regions of the mouse brain. We found substantial differences in 
effective attenuation coefficients among different brain areas, which lead to substantial 
differences in light intensity demands for optogenetic experiments. The use of light of 
different wavelengths additionally changes how light illuminates a given brain area. We 
created a brain atlas of effective attenuation coefficients of the adult mouse brain, and 
integrated our data into an application that can be used to estimate light scattering as well 
as required light intensity for optogenetic manipulation within a given volume of tissue. 

iii 



The form and content of this abstract are approved. I recommend its publication. 

Approved: Dr. Tim Lei 



iv 



DEDICATION 

I dedicate this work to those beloved ones whom I have lost and I still 
remember; to those who are suffering, not only every single day, but every single 
moment hoping that there will be a day in which researchers, like us, will come up with 
treatment for their illnesses to mitigate their suffering and alleviate their pain; to those 
whom I have promised that I am going to do my best in participating in whatever is going 
to be available for me to pave the way for breakthroughs that will lead to a better life with 
less pain and more pleasure for them and their dearest ones; to those whom I gave my 
words to that I will never let them down; to people whom I am always looking forward to 
putting a smile on their faces. 



V 



ACKNOWLEDGMENTS 

I acknowledge my fellowship from the Higher Committee for Education 
Development in Iraq (HCED). 

I would like to thank my consultant, advisor, and mentor. Dr. Tim Lei for all his 
encouragement, support, consultation, and advising that he has bestowed upon me 
throughout my graduate studies. Without his help, I would not have been able to spend 
my time, day by day, in a scientific and intellectual milieu which has been giving me the 
chance to learn from, study, meet, and collaborate with incredible researchers and 
students who have had a great influence on me. I am honored to work under his 
supervision. 

Here, I would also like to thank Dr. Achim Klug, Dr. Gidon Felsen, Dr. Anna 
Dondzillo, and Dr. Elizabeth Stubblefield for their collaboration in this work. I am 
indeed grateful for having this wonderful opportunity collaborating with all of them. It 
has been such an enriching experience being around people of knowledge like them. 



vi 



TABLE OF CONTENTS 



CHAPTER 

I. INTRODUCTION 1 

Optogenetics Era 1 

Neuroscience-Optogenetics Experimental Insights 3 

Main Goals of This Study 4 

Ethics Statement 5 

Animal Subjects 5 

Thesis Orientation 5 

n. EXPERIMENTAL SETUP, SAMPLE PREPARATION, TARGETED BRAIN 
AREAS, EXPERIMENTAL PROCEDURE, AND LIGHT PROFILE AND 
TISSUE DAMAGE CONTROL EXPERIMENTS 7 

Experimental Setup 7 

Optical Fiber Assembly 8 

Linearity Tests 11 

The Importance of These Linearity Tests 11 

LEDs Power Intensity Linearity Tests 11 

CCD Camera Linearity Tests 16 

Sample Preparation 19 

Targeted Brain Areas 20 

Experimental Procedure 21 

Manually-Controlled Method 21 

Pico-Motor-Controlled Fiber Punch-Through Method 23 

Light Profile and Tissue Damage Control Experiments 29 



m. DATA ANALYSES, THE MODIFIED BEER-LAMBERT LAW, BRAIN ATLAS 



ESTABLISHMENT, AND RESULTS 32 

Data Analyses 32 

The Modified Beer-Lambert Law and tlie Effective Attenuation Coefficients for 
Highly Scattering Neural Targets 38 

The Brain Atlas, and a Technique of Mapping the Effective Attenuation 
Coefficients across the Entire Brain 41 

The Effective Excitation Distance for Optogenetic Proteins 42 

Integration of All Relevant Data in a Computer Program 42 

Results 43 

Light Intensity Decreases Exponentially in Brain Tissue 44 

Light Scattering Properties Vary across Different Brain Regions 45 

Light Scattering Varies with Wavelength 49 

Light Scattering Brain Atlas 53 

Applying the Data to Experimental Design 56 

IV. DISCUSSION AND MAIN FINDINGS 61 

Discussion 61 

Main Findings 62 

V. IMPROVEMENTS, COMPARISON WITH PREVIOUS STUDIES, AND FUTURE 

PLANS 64 

Improvements 64 

Comparison with Previous Studies 65 

Future Plans 68 

Application of the Findings to Future Experiments 68 

Research Proposal for Determining Diffusivity Constants for Individual Brain 
Areas 69 



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REFERENCES 74 



ix 



LIST OF TABLES 



Table 

III. 1 Brain areas that were measured with three different wavelengths, and sample size 
(the unit of the effective attenuation coefficient is 1/mm) [12] 47 

V.l Midori-Ishi Cyan and mRFPl properties [21] 71 



X 



LIST OF FIGURES 



Figure 



II. 1 The experiment's desk showing the experimental setup equipment 7 

n.2 A 100 iim core, coupled to a 518 nm green LED and driven by a 100 mA current 
source, optical fiber output profile 9 

II. 3 A 100 core, coupled to a 518 nm green LED and driven by a 100 mA current 
source, optical fiber output profile after traversing a 100 iim sample thickness 9 

11.4 A 100 fim core, coupled to a 518 nm green LED and driven by a 100 mA current 
source, optical fiber output profile after traversing a 200 /^m sample thickness 10 

11.5 A 500 [im core, coupled to a 453 nm blue LED and driven by a 100 mA current 
source, optical fiber output profile after traversing a 100 [im sample thickness at 10 ms 
exposure time 10 

11.6 A 500 [im core, coupled to a 453 nm blue LED and driven by a 100 mA current 
source, optical fiber output profile after traversing a 100 [im sample thickness at 20 ms 
exposure time 1 1 

11.7 The data fitting line for the output power density of the 100 |jm core optical fiber, 
coupled to a 518 nm green (LED), when the room light is turned off 12 

II. 8 The data fitting line for the output power density of the 100 |jm core optical fiber, 
coupled to a 518 nm green (LED), under normal room's illumination 13 

II. 9 The data fitting line for the output power density of the 100 |.im core optical fiber, 
coupled to a 528 nm green (LED), when the room light is turned off 13 

II. 10 The data fitting line for the output power density of the 100 |im core optical fiber, 
coupled to a 528 nm green (LED), under normal room's illumination 14 

II. 1 1 The data fitting line for the output power density of the 100 |jm core optical fiber, 
coupled to a 453 nm blue (LED), when the room light is turned off 14 

11.12 The data fitting line for the output power density of the 100 |im core optical fiber, 
coupled to a 453 nm blue (LED), under normal room's illumination 15 

II. 13 The data fitting line for the output power density of the 500 |am core optical fiber, 
coupled to a 453 nm blue (LED), when the room light is turned off 15 

n.14 The data fitting line for the output power density of the 500 iim core optical fiber, 
coupled to a 453 nm blue (LED), under normal room's illumination 16 



xi 



11.15 Linearity test for the CCD camera at (100, 100) pixel's location of (1040 x 1392) 
pixel image 17 

11.16 Linearity test for the CCD camera at (100, 1292) pixel's location of (1040 x 1392) 
pixel image 17 

11.17 Linearity test for the CCD camera at (520, 696) pixel's location of (1040 x 1392) 
pixel image 18 

11.18 Linearity test for the CCD camera at (940, 100) pixel's location of (1040 x 1392) 
pixel image 18 

11.19 Linearity test for the CCD camera at (940, 1292) pixel's location of (1040 x 1392) 
pixel image 19 

11.20 Light arbitrary digital intensity as a function of tissue's thickness for a PPT region. 
This is a one single set of measurements 22 

n.21 Basic experimental setup of the punch-through method. On an inverted microscope, 
an optical fiber was placed on a section of brain tissue such that light from the fiber 
would pass through the tissue and subsequently be imaged by an objective attached to a 
CCD camera [12] 24 

11.22 A snap shot for the controlling program front panel expressing the adjustable 
significant parameters and other details 26 

11.23 An example of an original image captured by the CCD camera, showing light 
emitted from an optical fiber after it passed though a section of brain tissue [12] 27 

n.24 Optical transmittance as a function of tissue thickness. As the optical fiber was 
advanced through the section of brain tissue and repeated images such as the one in 
figure 11.23 were taken, the decrease in optical transmittance as a function of tissue 
thickness could be evaluated. The single measurements ("+" symbols) represent 
transmittance of blue light (453 nm) through a section of PPT at various thicknesses, 
while the solid line represents an exponential fit [12] 28 

11.25 (Left) it is an overlapped picture of two images that are taken for a PPT region, in 
300 |jm of thickness and 1300 |.im from the midline of depth slide. The background 
image (which is in black and white colors) shows the PPT area, while the blue one is, the 
output optical power intensity profile for the 100 |jm core optical fiber connected to a 453 
nm blue LED, driven by a 28 mA current source. This picture is evidence that the blue 
LED light is not sufficient to cover the whole PPT region. These two images are taken on 
an integration time of 100 ms. (Right) it is an overlapped picture of two images that are 
taken for a PPT region, in 300 |jm of thickness and 1300 |jm from the midline of depth 
slide. The background image (which is in black and white colors) shows the PPT area, 
while the green one is, the output optical power intensity profile for the 100 |^m core 
optical fiber connected to a 518 nm green LED, driven by a 100 mA current source. This 



xii 



picture is evidence that the green LED light is not sufficient to cover the whole PPT 
region. These two images are taken on an integration time of 100 ms 29 



n.26 (Top left) a 300 |am of thickness and a 1500 ^m from the midline of depth slide's 
image, showing the actual image that is taken from the CCD camera, of the CAS 
Hippocampus region under white light illumination and before the laser damage. This 
image is taken on an integration time of 100 ms. (Top right) a 300 |am of thickness and a 
1500 iim from the midline of depth slide's image, showing the false color of the CA3 
Hippocampus region under white light illumination and before the laser damage. This 
image is taken on an integration time of 100 ms. (Bottom left) a 300 |jm of thickness and 
a 1500 fim from the midline of depth slide's image, showing the actual image, that is 
taken from the CCD camera, of the CA3 Hippocampus region under 405 nm and 3.5 mW 
laser source illumination, being applied for 3 minutes of time. The image shows a real 
tissue damage which is caused by the laser source under these circumstances. This image 
is taken on an integration time of 100 ms. (Bottom right) A 300 |jm of thickness and a 
1500 |am from the midline of depth slide's image, showing the false color of the CA3 
Hippocampus region under 405 imi and 3.5 mW laser source illumination, being applied 
for 3 minutes of time. The image shows a real tissue damage which is caused by the laser 
source under these circumstances. This image is taken on an integration time of 100 ms30 

ni. 1 A snap shot for the viewer program front panel screen that is used for retrieving the 
intensities from the images and plotting them as a function of tissue thickness according 
to the specific cursor location 33 

ni.2 A cerebellum one raw data and fitting curve. Note the offset in the fit. This issue 
will be addressed below 35 

ni.3 A comparison between PPT one and PPT two. Note the offset in the fit. This issue 
will be addressed below 36 

111.4 A comparison between CA3 one and CA3 two. Note the offset in the fit. This issue 
will be addressed below 36 

111.5 A comparison between PPT one and PPT two after taking the offset factor Yo into 
account which demonstrates its significant impact on the reanalyzed and refitted the data 
37 

111.6 A comparison between CA3 one and CA3 two after taking the offset factor Yo into 
account which demonstrates its significant impact on the reanalyzed and refitted the data 
38 

111.7 Optical transmittance through different types of brain tissue. Measurements using 
the fiber punch-through technique were taken in eight different brain areas with blue (453 
nm) light. In each case, optical transmittance decreased exponentially with tissue 
thickness; however, the exponential decreases observed varied greatly with the type of 
tissue. Single measurements are represented by the respective symbols while the solid 
lines represent exponential fits of the data 45 

xiii 



III.8 Effective attenuation coefficients with SEMs for the eight brain areas: VNTB 19.96 
+/- 0.26 (1/mm); CAS 19.12 +/- 0.84 (1/mm); MNTB 18.16 +/- 0.69 (1/mm); LSO 17.92 
+/- 0.80 (1/mm); PPT 15.26 +/- 0.78 (1/mm); OB 14.88 +/- 0.74 (1/mm); SC 13.91 +/- 



0.83 (1/mm); Cerebellum 9.76 +/- 0.78 (1/mm) 46 

III. 9 Optical power values that would need to be fed into a 100 |j,m diameter optical fiber 
when 300 f^m of tissue needs to be illuminated at intensities typically used for 
Channelrhodopsin activation 48 



III. 10 Same as figure III.l 1 except that in this example the illumination was calculated to 
hypothetically activate Channelrhodopsin over a distance of 600 ^m trom the fiber tip . 49 

III. 1 lEffects of wavelength on optical transmittance. Optical transmittance in the MNTB 
as a function of tissue thickness and optical wavelengths. The three colorcoded data sets 
represent corresponding measurements with light of three different optical wavelengths 
(blue (453 nm), green (528 nm), and red (940 nm)). Longer-wavelength light penetrates 
tissue deeper, resulting in a higher transmittance at any given tissue thickness [12] 50 

III. 12 Optical transmittance in the VNTB as a function of tissue thickness and optical 
wavelengths. The three colorcoded data sets represent corresponding measurements with 
light of three different optical wavelengths (blue (453 nm), green (528 nm), and red (940 
nm)). Longer-wavelength light penetrates tissue deeper, resulting in a higher 
transmittance at any given tissue thickness 51 

III. 13 Effects of light wavelength on transmittance in two brain areas (MNTB and 
VNTB). The effective attenuation coefficient decreases with wavelength for the three 
wavelengths tested. MNTB measurements are represented by round symbols while 
VNTB measurements are represented by square symbols. Measurements in the three 
different colors are indicated by the color-code of the symbols [12] 52 

III. 14 MNTB and VNTB proposed fitting curves for the effective attenuation coefficients 
as a function of wavelengths 52 

III. 15 Relating fiber punch-though measurements to brain atlas measurements. An image 
of a 300 ixm coronal section of mouse brain stem, taken on a calibrated virtual 
microscopy system with monochromatic light. Areas with higher optical transmittance 

appear brighter on the image, while areas with lower transmittance appear darker. 
MNTB, VNTB, and LSO are outlined in red, orange, and yellow, respectively [12] 54 

ni.16 Correlation in digital irradiance for brain areas tested with both the fiber punch- 
through and the virtual microscopy method. Digital irradiance was measured in six brain 
areas (MNTB (red), VNTB (orange), LSO (yellow), PPT (green), SC (light blue), and 
cerebellum (dark blue) with both the fiber punch through and the virtual microscopy 
technique. Results were normalized and plotted against each other. Each colored symbols 
represents the measurements from one brain area with two methods, the solid line 
indicates complete overlap between the measurements. The bars attached to each data 
point represent the standard error [12] 55 



xiv 



ni.19 The desired input parameters control panel 



57 



111.20 The attainable penetration depth as a function of optical power at the fiber tip for 
the desired entered input parameters 58 

111.21 A sample image from the brain atlas where the investigator can select the area of 
interest precisely such that its optical properties are designated, and the corresponding 
penetration depth and optical power at the fiber tip are calculated, accordingly 59 

111.22 A screenshot for the user manual that is available in the computer program also, in 
which the user can be taken through details about how to use this application to its full 
extent 60 

V. 1 A comparison between our exponential fit and Kubelka-Munk fit for a PPT raw data 
showing that it is best fitted with a single exponential curve 66 

V.2 A comparison between our exponential fit and Kubelka-Munk fit for an MNTB total 
intensity measurements of the raw data averaged over the entire detector's area showing 
that it is best fitted with a single exponential curve 67 

V.3 MiCy excitation and emission spectra [22] 71 

V.4 mRFPl absorption (solid line), excitation (dotted line), and emission (dashed line) 
spectra [23] 72 

V.5 ChR2 and NpHR activation spectra [4] 72 



XV 



CHAPTER I 



INTRODUCTION 

Optogenetics Era 

Deep brain stimulation (DBS) technology is one of the most effective 
technologies that have been used as a treatment and a cure for a wide spectrum of 
psychiatric disorders and diseases. The key function of this technology is making various 
kinds of stimulation to specific defective areas that are responsible for certain brain's 
functions by either activate or deactivate them to compensate for the malfunction that is 
happening in them. The conventional approach to this technology is by doing the stimuli 
electrically by inserting metal electrodes in those areas and implementing that required 
current intensity to achieve the pre-decided aim. However, as one can see, there are some 
downsides to this method though. Cells damage, corrosions, tumors. . .etc., are 
predisposed by this invasive method [1]. It might also have a severe effect on the 
surrounding and the intact cells. In addition, metal electrodes can not specifically target a 
certain cell type in the neural target, making the treatment much less specific and could 
lead to adverse treatment outcomes. Moreover, it is not possible to specifically control 
stimulation or suppression of the neural signals in the brain. Nonetheless, DBS using 
metal electrodes is the current state-of-the-art method of deep brain stimulation. After 
discovering some photosensitive materials especially photosensitive proteins that could 
be latched on cells and cells' membranes, the idea of using light to do the same required 
stimuli, but this time optically, came out to the surface as a safer and noninvasive 
breakthrough to deal with these conditions and diseases [2]. In this method, the light is 

1 



shining specific areas which have already those photosensitive proteins, and some parts 
of the neural networks start to fire or suppress that firing and control some brain 
functions to deliver the desired treatment. This is what is called "optogenetic" technique, 
in brief! [2] And nowadays, it is considered as one of the recent cutting edge technologies 
in this field. And from this point forward, manipulating neural function with light is 
becoming an increasingly important technique. This is particularly important for this 
recently emerging field of optogenetics, which provides powerful tools to either activate 
or suppress neural activity with light at a relatively fast time scale (sub-millisecond) (e.g. 
[3]-[5]). Controlling neuronal firing with light has opened up not only a number of 
exciting new avenues to study neural circuits, but also treatment options of a number of 
medical conditions such as Parkinson's disease or certain forms of blindness [6]-[8]. 

As it has been known for the conventional approach that the amount of charge 
intensity will specify the demanded treatment as the brain areas have different electrical 
properties, the amount of light (or the light intensity) required to serve the same purpose 
should be pre-specified as well, as those brain areas may show different optical 
properties. Having said that, the first question that have been asked is; how much optical 
power intensity that is required to deliver light to a specific neural target with a specific 
optical penetration depth to get the stimulation, activation or deactivation, and the neural 
responses desired will be. After determining this amount of the power intensity required 
to do the process, the second question is, what is the initial optical power intensity that 
the physician should start with at the outer boundary of the neural target- as it is not 
preferable to punch through it, yet instead, shining light directly on top of it. 



2 



The latter question requires the knowledge of the optical properties for those areas 
under study or investigation, because it is related to the light transmission, absorption, 
and the scattering phenomena that are happening within the targeted area. Therefore, the 
idea of having a three-dimensional (3D) light scattering model has become a necessity in 
order to give a comprehensive expectation of how light behaves inside different brain 
areas. Yet, it has been required to collect the constructing optical parameters of this light 
scattering model. Thus, the scientific journey has started by conducting this study to 
achieve this goal by extracting the effective attenuation coefficient (/it) which is one of 
the main optical parameters that this model will be composed of. 

Neuroscience-Optogenetics Experimental Insights 

For experiments using cell cultures or brain slices, the precise and reliable 
delivery of light to the neurons to be manipulated is relatively simple and is typically 
achieved by attaching a suitable light source to a microscope, and subsequently 
delivering light stimuli with the desired parameters directly to the neural tissue. For in- 
vivo experiments, however, light delivery to deep brain areas is much more challenging. 
Typically, investigators use stereotaxic methods to place an optical fiber just above the 
brain neural target to be illuminated, such that light emitting from the fiber effectively 
illuminates the tissue below the fiber tip [9]. 

Depending on the optical properties of the specific tissue, light emitted from the 
fiber tip propagates deeper or less deep through the tissue, with neurons more distant 
from the fiber tip receiving higher or lower light intensities. All light sensitive molecules 
(such as the various opsins typically used in optogenetic experiments, but also caged 
compounds and fluorescent dyes) have a threshold of activation, (for the purpose of this 

3 



publication defined in practical terms as the minimum light intensity required to 
effectively trigger or inhibit the desired neural action potential). Therefore, light sensitive 
molecules can only be activated at a certain maximum distance from the light source, and 
this distance depends on both the optical properties of the tissue and the activation 
threshold of the molecule used in the experiment. Most studies involving delivery of light 
to deep brain areas assume, for simplicity, that all brain tissue scatters light in the same 
way, i.e. different brain areas behave similarly if not identically as far as light 
propagation in the tissue is concerned [1], [10], [11]. However, some brain areas consist 
primarily of cell bodies while others consist primarily of neural fibers, and some brain 
areas with significant myelination appear darker while others appear lighter when 
observed under a microscope with transmitted light, suggesting differences in optical 
properties between different brain areas. 

Main Goals of This Study 

The primary goal of this study was to test the h5^othesis that different brain areas 
scatter and propagate light to different degrees. If correct, specific knowledge about the 
brain area to be manipulated would be required for the appropriate design of 
experimental manipulations. A secondary goal of the study was to create an easy to use 
computer program to estimate light scattering values for different areas of the mouse 
brain that could be used as a reference in future experiments. 

Our experimental approach was to use sections of fresh brain tissue in 
combination with light emitting optical fibers that were advanced through the tissue to 
precisely measure light scattering properties. The results presented here are supplemented 
with a light scattering mouse brain atlas programmed as an iPhone application. These 

4 



tools are intended to aid an investigator in determining the required light intensity to be 
delivered for successful optogenetic manipulation. 

Ethics Statement 

All animal procedures were approved by the Institutional Animal Care and Use 
Committee (lACUC) of the University of Colorado Medical Campus (Permit number B- 
88412(05) ID. Furthermore, all applicable laws and regulations, as well the PHS Policy 
were strictly followed. 

Animal Subjects 

34 male and female C57BL/6J mice were used in these experiments. All animal 
procedures were approved by the University of Colorado Institutional Animal Care and 
Use Committee, and were conducted in accordance with National Institutes of Health 
standards on humane treatment of laboratory animals. 

Thesis Orientation 

In the following chapters, the experimental setup, sample preparation, targeted 
brain areas, and experimental procedure needed to measure effective attenuation 
coefficients will be presented (Chapter II). The results of these sets of experiments and 
the brain atlas establishment will be shown, as well, in both graphical and numerical 
presentations in Chapter III. These results will also be discussed, summarizing the main 
findings of this study, in Chapter FV, and some impairment will be illustrated in one of 
these sections. Finally, solutions for those difficulties that have worked out so far, 
improvements that have been come up with, some other suggestions, comparison with 
previous studies, and future plans (research proposal for gathering more parameters to 

5 



perfect a three-dimensional (3D) light scattering model of the mouse brain) will also be 
available to the researcher in Chapter V. 



6 



CHAPTER II 



EXPERIMENTAL SETUP, SAMPLE PREPARATION, TARGETED 
BRAIN AREAS, EXPERIMENTAL PROCEDURE, AND LIGHT 
PROFILE AND TISSUE DAMAGE CONTROL EXPERIMENTS 

Experimental Setup 

The experimental setup is mainly composed of the following devices: an inverted 
microscope (Nikon Diaphot 200, Nikon Corp., Japan) with a monochromatic 12bit 
Charged-Coupled Device (CCD) camera (Mightex CCE-B013-U) attached to it, a current 
derive source- a Mightex LED power supply (SLB- 1200-1)- which derives the optical 
fibers, a computer, a CCD video camera and a monitor. The latter two components have 
been added afterward to adjust the fiber tip precisely on top of the sample before starting 
running the experiment. The investigational bench is pictured in figure II. 1. 




Figure 11. 1 The experiment's desk showing the experimental setup equipment 

7 



Optical Fiber Assembly 

Three different optical fiber assemblies were used for the measurements. All three 
assemblies consisted of 100 i^m core diameter optical fibers (UM22-100, Thorlabs, 
Newton, NJ)) attached to 453 nm (blue), 528 nm (green), and 940 nm (near infra-red) 
LEDs, respectively. All LEDs were purchased from Digikey (Thief River Falls, MN). 
The optical fiber was lined up with its respective LED using two precision manipulators. 
The alignment was carefully done to obtain maximum optical throughput but avoiding 
crashing the fiber tip into the LED. UV optical epoxy was used to set the optical fiber in 
place and to secure the alignment between the LED and the optical fiber. In each case, the 
LED-optical fiber assemblies were powered by the Mightex LED power supply, allowing 
the optical power output to be adjusted by changing the electrical current running through 
the LEDs. Each and every experiment, the fiber optics should be examined not only to 
make sure that the output optical power intensity is steady but also the fiber tips are still 
intact and having a uniform light profile. Figure 11.2 shows the optical fiber output light 
profile, whereas figure II.3 and figure II.4 illustrate how this light profile would be after 
traveling through 100 [im and 200 iim tissue thickness for the same exposure time (2500 
ms). Another example when the exposure time has changed for the same tissue thickness 
is presented in figure 115 and figure n.6. 



8 



1DZI micromeler core, optical fihier oulput profile, coLpled to 518 nrr, green [LED) driuen by a 1 GO mA current source, at esposure time equals to 50D ms 




Figure II.2 A 100 fim core, coupled to a 518 nm green LED and driven by a 100 mA 
current source, optical fiber output profile 




Figure II.3 A 100 fim core, coupled to a 518 nm green LED and driven by a 100 mA 
current source, optical fiber output profile after traversing a 100 fim sample 
thickness 



9 




Figure II.4 A 100 nm core, coupled to a 518 nm green LED and driven by a 100 mA 
current source, optical fiber output profile after traversing a 200 fim sample 
thickness 




Figure II.5 A 500 fim core, coupled to a 453 nm blue LED and driven by a 100 mA 
current source, optical fiber output profile after traversing a 100 fim sample 
thickness at 10 ms exposure time 



10 




Figure II.6 A 500 fim core, coupled to a 453 nm blue LED and driven by a 100 mA 
current source, optical fiber output profile after traversing a 100 fim sample 
thickness at 20 ms exposure time 



Linearity Tests 

The Importance of These Linearity Tests 

Now that these first sets of graphs had been collected and made as empirical 
references for the next following sets of experiments that have been launched after. And 
that has given the flexibility required to modify and adjust some experimental parameters 
without changing the setup or the procedure entirely. In addition to that, comparable 
ways of presenting the analyzed data and the results have been allowed by the aid of 
those graphs. 

LEDs Power Intensity Linearity Tests 

Four different types of optical fibers coupled to four different LEDs having 
different wavelengths had been tested to incorporate within this experiment; those fibers 

11 



are: green 518 (nm), 100 (|am) core diameter, green 528 (nm), 100 (|im) core diameter, 
blue 453 (nm), 100 (|am) core diameter, blue 453 (nm), 500 (i^m) core diameter. The 
power intensity graph as a function of current intensity had been measured for those four 
optical fibers and drawn as they can be seen in the following figures. The CCD camera 
sensitivity for LEDs power intensity linearity responses under normal room's 
illumination versus when the room light is turned off had been tested taking into account 
the different LEDs wavelengths and different optical fibers core diameters. The results 
show very reliable linearity responses for the camera. 




50 100 150 

Current (mA) 



Figure II.7 The data fitting line for the output power density of the 100 |iim core 
optical fiber, coupled to a 518 nm green (LED), when the room light is turned off 



12 



+ data1 




50 100 150 

Current (mA) 



Figure II.8 The data fitting line for the output power density of the 100 |iim core 
optical fiber, coupled to a 518 nm green (LED), under normal room's 
illumination 



xlO 

I ^ ^ il 

+ datal - 




linear 



SO 100 150 

Current (mA) 

Figure II.9 The data fitting line for the output power density of the 100 |iim core 
optical fiber, coupled to a 528 nm green (LED), when the room light is turned off 



13 




Figure 11.10 The data fitting line for the output power density of the 100 |nm core 
optical fiber, coupled to a 528 nm green (LED), under normal room's 
illumination 




Figure 11.11 The data fitting line for the output power density of the 100 |iim core 
optical fiber, coupled to a 453 nm blue (LED), when the room light is turned off 



14 




Current (mA) 



Figure 11.12 The data fitting line for the output power density of the 100 |iim core 
optical fiber, coupled to a 453 nm blue (LED), under normal room's illumination 




Figure 11.13 The data fitting line for the output power density of the 500 |iim core 
optical fiber, coupled to a 453 nm blue (LED), when the room light is turned off 



15 



2.5 



.x10 



I 

c 
Q 

oi 


CL 



1.5 



y= 1.5e-005*x + 0.0002 


+ data1 
linear 













50 



100 



Current (mA) 



Figure 11.14 The data fitting line for the output power density of the 500 |iim core 
optical fiber, coupled to a 453 nm blue (LED), under normal room's illumination 



CCD Camera Linearity Tests 

The CCD camera linearly tests had also been experimented as a function of 
various exposure times and these graphs can be shown in the following figures. Five 
different pixel locations had been taken into consideration which are (100, 100), (100, 
1292), (520, 696), (940, 100), and (940, 1292) of (1040 x 1392) pixels image to show the 
consistency and robustness of the linearity responses across the entire detection area. 



16 



3000 



2500 



2000 



^ 1500 

X 

5 1000 



500 



y = 0.53815*x + 144.84 


III 


+ datal , 
linear 




.^^^Jr^. 










+ ^ 






i 1 1 1 



500 1000 1500 2000 2500 3000 3500 4000 4500 5000 

Exposure Time (ms) 



Figure 11.15 Linearity test for tlie CCD camera at (100, 100) pixel's location of (1040 
X 1392) pixel image 



3000 



2500 



2000 



% 1500 

X 

5 1000 



500 



y = 0.48587*x + 141.35 










+ datal 
linear 










































+ A 

























500 1000 1500 2000 2500 3000 3500 4000 4500 5000 

Exposure Time (ms) 



Figure 11.16 Linearity test for the CCD camera at (100, 1292) pixel's location of 
(1040 X 1392) pixel image 



17 




Figure 11.17 Linearity test for tlie CCD camera at (520, 696) pixel's location of (1040 
X 1392) pixel image 




Figure 11.18 Linearity test for the CCD camera at (940, 100) pixel's location of (1040 
X 1392) pixel image 



18 



2500 

2000 

S 1500 

y 

b. 

^ 1000 
b 

500 



"0 500 1 000 1 500 2000 2500 3000 3500 4000 4500 5000 

Exposure Time (ms) 

Figure 11.19 Linearity test for the CCD camera at (940, 1292) pixel's location of 
(1040 X 1392) pixel image 

Sample Preparation 

Another significant and vital part before initiating these experiments is the case 
study sample preparation. This operation has had a lot of impacts on the results, on the 
whole, and during the course of action through conducting these experiments. This 
process is started by getting the animal down, decapitated, after being briefly anesthetized 
via isoflurane inhalation (IsoFlo, Abbott Laboratories, USA). All animals that are 
allocated for those sets of experiments were six to eight weeks old mice from which 
coronal and sagittal brain slices were prepared. Then the brain is being taken out of the 
skull through a neat procedure and was dissected out under ice-cold dissection Ringer 
containing either (in mM): Ringer 1: 125 NaCl, 2.5 KCl, 1 MgCb, 0.1 CaCb, 25 glucose, 
1.25 NaH2P04, 25 NaHCOs, 0.4 ascorbic acid, 3 myo-inositol, and 2 pyruvic acid; or 
Ringer 2: 200 sucrose, 1.25 NaH2P04, 26 NaHCOa, 10 glucose, 3.5 KCl, 7 MgCl, 1.5 
ascorbic acid (all chemicals from Sigma). After that, it's adhered and sliced using the 

19 



y= 0.^ 


099*x + 1 22 


.94 














+ datal 
linear 







































slicing machine to different slices thicknesses (mainly 600 |jm). Those slices were cut 
with a vibratome (VTIOOOS, Leica), transferred to an incubation chamber containing 
extracellular solution (ECS) [ECS; containing (in mM) 125 NaCl, 2.5 KCl, 1 MgCh, 2 
CaCh, 25 glucose, 1.25 NaH2P04, 25 NaHCOs, 0.4 ascorbic acid, 3 myo-inositol, and 2 
pyruvic acid, all chemicals from Sigma] and bubbled with 5% C02-95% O2. Slices were 
incubated in ECS for 15 - 30 minutes at 37°C and then cooled down to room temperature. 
All measurements were obtained within 2-3 h of slicing. 

Targeted Brain Areas 

The brain areas that have been dealt with throughout this study are: Medial 
Nucleus of the Trapezoid Body (MNTB), Ventral Nucleus of the Trapezoid Body 
(VNTB), Lateral Superior Olive (LSO), Pedunculopontine Tegmental nucleus (PPT), 
Superior CoUiculus (SC), Comu Ammonis 3 of hippocampus (CA3), the cerebellar 
cortex molecular layer. Olfactory Bulb (OB). The brain regions were chosen because 
previous knowledge suggested that they would represent a wide range of scattering 
coefficients, but also to perform control experiments for future optogenetics 
manipulations. 

And since in these experiments, the thicknesses of the samples play a significant 
role in determining how the results would look like, this issue has been always borne in 
mind and taken into account by having those brain areas completely confined within the 
sample thickness, by making its surface as a flat as it could be, and by immersing it in the 
ECS while doing the slicing process and when the measurements are being taken. 
Moreover, sometimes it's also being bubbled throughout the experiment to keep it 
oxygenated. The truth of the matter behind these strict sample preparations is the 

20 



tendency to mimic almost the same "in vivo" environment and maintain the metabolism 
of the sample as long as possible. This study has shown how this aspect has an absolute 
relevance with how those biological tissues respond optically (more details will be 
presented in the discussion section). 

Experimental Procedure 

Manually-Controlled Method 

After the sample is prepared with a certain thickness, it is transferred to a small 
chamber that is transparent from the bottom to make it more convenient for using with 
the inverted microscope. That chamber will have been already cleaned using special lens 
papers. The sample will be floating inside the preserving fluid (that is bubbled sometimes 
to keep it oxygenated and healthy, as it is mentioned before). And for that reason, it is 
required to add a piece of metal with strings as a mass to keep it from that random 
movement. However, the latter has undesirable effects on the sample as well; these 
effects will be elucidated in the discussion section. The earlier stages of these sets of 
experiments had been done manually without having a pico-motor and the CCD video 
camera and the monitor, by trying to land the fiber tip on the top of the sample and get it 
to be centered on the targeted area without forgetting having the sample being in focus by 
moving the stage up and down, and take an image that represents arbitrary digital 
intensities for the original optical power intensities after passing through that specific 
thickness. Then, that sample will be replaced by another one with another thickness and 
the same procedure is being repeated. The current intensity that is corresponding to the 
aimed optical power intensity is set up based on the optical power intensities curves for 

21 



each individual optical fiber. Room's lights will be turned off to avoid any other 
illumination sources. The main goal for those types of experiments was to construct a 
curve for the arbitrary digital intensities or the optical power intensities as a function of 
sample thickness. Each point accounts for the maximum intensity accompanied with the 
fact that this fiber optic output profile is Gaussian (Some results belongs to this approach 
can be seen in figure 11.20). 



3000 



2500 ■ 
>. 2000 ■ 



1000 ■ 
500 ■ 




Q I I I I I I I 

200 300 400 500 600 700 800 900 
Tissue Thickness (micrometer) 



Figure 11.20 Light arbitrary digital intensity as a function of tissue's tliickness for a 
PPT region. This is a one single set of measurements 

As it stated earlier, the first sets of experiments had been performed without 

having the pico-motor which is implemented later in order to make punching through the 

brain's samples possible with higher accuracy (see next section). Before that, all the 

punching trials had been done manually which had been considered to be a vague process 

since there are no enough clues to determine how far the fiber tip inside the sample goes. 

22 



Pico-Motor-Controlled Fiber Punch-Through Method 

The other approach that has been launched after that pico-motor and the CCD 
video camera had been installed to the system is the punching through approach or "fiber 
punch-through method". In this approach, instead of having several samples with 
different thicknesses in order to construct that formerly mentioned graph, there will be 
only one sample with the thickness that contained the whole area under investigation 
from the top to the bottom, and now the fiber tip can punch through driven by that pico- 
motor through precisely determined step sizes to trace the total moving distance after 
making sure that the fiber tip is properly landed on the top of the sample surface. 

After the incubation period, a slice was placed into a measurement chamber and 
continuously superfused with bubbled extracellular solution for the duration of the 
experiment. The measurement chamber was then positioned on the inverted microscope 
in which the standard transmitted light source was replaced by an assembly consisting of 
a three-axis manual micromanipulator (Narishige model MM-3), a calibrated piezo 
driven one axis micromanipulator (Model 8302 Picomotor Actuator, Newport, Irvine, 
CA), and a custom made optical fiber holder to hold one of the three fiber/LED 
assembUes in place. The output end of the optical fiber was placed directly onto the 
surface of the brain slice under the guidance of the CCD video camera using macro 
optics, such that the emitted light was facing the brain section and the microscope's 
objective (EF lOx, N.A. 0.25, Leitz Wetzlar, Germany). The light was then captured by 
the monochromatic 12bit camera attached to the microscope via the camera port (see 
figure n.21 for a sketch of the setup). 



23 



Glass slide 



Light ' 
source 





Optical fiber 



Section 
600|jnn thick 



Objective xlO 
N.A. 0.25 



Monochrome 
12 bit camera 



Figure 11.21 Basic experimental setup of the punch-through method. On an inverted 
microscope, an optical fiber was placed on a section of brain tissue such that 
light from the fiber would pass through the tissue and subsequently be imaged 
by an objective attached to a CCD camera [12] 

Exposure time and the irradiance of the optical fiber (/oj were adjusted to 
optimally utilize the Mightex camera dynamic range throughout the entire data set. 
Subsequently, the fiber was lowered into the slice in 5 [xm steps using the precision piezo 
micromanipulator, starting from the surface of the section and ending at a depth of 500 
\im. At every step, the camera will be taking a number of images and get them to be 
averaged by a number, which can be manipulated from the controlling program front 
panel. Instantaneously, a graph will be drawn for arbitrary digital intensities as a function 
of sample thickness after allocating the cursor in the right position. Consequently, the 
images taken will be stored in a chosen folder to pave the way for more data analysis to 
be accomplished upon them succeedingly. 



24 



Computer software. Lab VIEW 2009 Service Pack 1 (National Instruments, 
Austin, TX), has been installed on the computer, and a computer program was written in 
this software to control the pico-motor and get it to move up and down in very precise 
step sizes, and to control the Mightex camera. Other very important parameters can be 
changed or adjusted through the program panel; for example, the CCD camera exposure 
time, total moving distance, the number of pictures that are going to be taken and 
averaged for each individual step size measurement. It is also allowed to change the 
cursor position to another pixel location rather than the central one to read the digital 
intensities from those pixels locations (a snap shot for the controlling program front panel 
screen can be seen in figure 11.22). 



25 



i Tiiiue Light Seal 


eri 


ng Control ProBram 


vi Front Panel 
































File Edit View Projeci: Operate Tools Windo 


Help 




































^ 


Mm 


II 1 1 13pi: Application Font 
































able Camera 










H 


Mil 












Intensity at Cursor 


H 


1 1 i 1 1 1 


1—1 


H 
















e Time (ms) 


















































^-4094 


























— teae- 


-W9B 


— 36136 — ■ 




& 


5006 












1606- 
















































































































i 
























"CGDModuleNtji 




























900- 
650- 














































1 


































































800- 




















































n ■^wiriiNiTr: 






















750- 
700- 
656- 
























1 




























































i 










































































Motor COM Po 


t 






















600- 
550- 




































































4 






































































































506- 














































































456- 
406- 
350- 
300- 
250- 
200- 
150- 
100- 
50- 




















































Sl:ep Sise [um 










Average number 
10 








































Move Moto 


(um) 




















Total DistancE 


to n 


easure 


[um) 






























\- 




- 












Current Step 














Motor Move | 
















' MEASURE 












































renarfie coiawe maqn 
























1392 


1300 1200 


1100 


1000 900 


3 


70i: 


600 SOO 400 300 200 100 ( 






















Desktop\test\test 

I 


_ 














Cursors: 






if 


|Z 1 


1 


1 






































S 

1 


Cursor 


742 


535 


2214 








^1 




















Wait Time for Motor (ms) 
































1 1 


















































Q 


























4500- 










PlotO 










































































5T0P 1 




















40Q0- 
3500- 
3000- 










t 
























































































































































1 


20 


0- 






























































15 
10 
5 


































































JjJjJ- 










0- 
0- 
















































- 


































0- 


50 


60 156 


206 256 300 350 460 450 500 
listance (um) 
































i 
















H 


















































































































































































































































































































































































Main 


Application Instance 


< .> 








Ti55ue Light Scatter 




I 




Light 5catterin 




> LabVlEV 




















V • a s eg s 


22 P 





Figure 11.22 A snap shot for the controUing program front panel expressing the 
adjustable significant parameters and other details 

Images taken at different steps were stored for further data analysis. An example 
of such an image is shown in figure 11.23. 



26 



Figure 11.23 An example of an original image captured by the CCD camera, 
showing light emitted from an optical fiber after it passed though a section of 
brain tissue [12] 

The data was extracted from images by locating the pixel representing the fiber 
center, and collecting that pixel 12 bit gray scale value for the digitized optical irradiance 
/(z). This process was repeated for each image, /(z) was normalized to to obtain the 
optical transmittance r(z) = /(z)//^, which was then fitted by a single exponential 
function (Figure 11.24) according to the modified Beer-lambert law (see Chapter III) to 
extract the effective attenuation coefficient p.effOf the measured neural target. 



27 




Tissue Thickness (pm) 



Figure 11.24 Optical transmittance as a function of tissue thickness. As the optical 
fiber was advanced through the section of brain tissue and repeated images such 
as the one in figure 11.23 were taken, the decrease in optical transmittance as a 
function of tissue thickness could be evaluated. The single measurements ("+" 
symbols) represent transmittance of blue light (453 nm) through a section of 
PPT at various thicknesses, while the solid line represents an exponential fit [12] 

Eventually, the output optical power intensity and the light profile will be tested 
again to be certain that the fiber tip has not been defected and the light profile is not 
distorted throughout the experiment. 

Control experiments determined that the forces applied on the tissue by the 
advancing glass fiber are comparable to those created by an advancing sharp 
microelectrode (< 200 |xN, data not shown). We thus concluded that lowering the fiber 
into the tissue caused the fiber tip to slice through, rather than squish the tissue together, 
such that measurements at many different tissue thicknesses could be taken reliably from 
the same tissue section at precisely controlled depths (referred to as "fiber punch-through 
method"). 

28 



Light Profile and Tissue Damage Control Experiments 

Incidentally, and as it is referred to the idea of whether the light profile is enough 
to cover the targeted areas or not, it is convenient to show the results regarding this part 
of the study as shown in figure 11.25. 




200 400 BDD 800 1000 120D 200 400 BOO 800 1000 1200 



Figure 11.25 (Left) it is an overlapped picture of two images that are taken for a PPT 
region, in 300 |iim of thickness and 1300 |iim from the midline of depth slide. The 
background image (which is in black and white colors) shows the PPT area, 
while the blue one is, the output optical power intensity profile for the 100 |iim 
core optical fiber connected to a 453 nm blue LED, driven by a 28 mA current 
source. This picture is evidence that the blue LED light is not sufficient to cover 
the whole PPT region. These two images are taken on an integration time of 100 
ms. (Right) it is an overlapped picture of two images that are taken for a PPT 
region, in 300 |iim of thickness and 1300 |iim from the midline of depth slide. The 
background image (which is in black and white colors) shows the PPT area, 
while the green one is, the output optical power intensity profile for the 100 |iim 
core optical fiber connected to a 518 nm green LED, driven by a 100 mA current 
source. This picture is evidence that the green LED light is not sufficient to cover 
the whole PPT region. These two images are taken on an integration time of 100 
ms 

Another potential trial which has emerged from the eagerness of showing how the 
laser light intensity could expose a thermal damage in the targeted area had been 
performed and its results are nicely presented in figure 11.26. 



29 




Figure 11.26 (Top left) a 300 |iim of thickness and a 1500 |iim from the midline of 
depth slide's image, showing the actual image that is taken from the CCD 
camera, of the C A3 Hippocampus region under white light illumination and 
before the laser damage. This image is taken on an integration time of 100 ms. 
(Top right) a 300 |iim of thickness and a 1500 |iim from the midhne of depth 
slide's image, showing the false color of the CA3 Hippocampus region under 
white light illumination and before the laser damage. This image is taken on an 
integration time of 100 ms. (Bottom left) a 300 |iim of thickness and a 1500 |iim 
from the midline of depth slide's image, showing the actual image, that is taken 
from the CCD camera, of the CA3 Hippocampus region under 405 nm and 3.5 
mW laser source illumination, being applied for 3 minutes of time. The image 
shows a real tissue damage which is caused by the laser source under these 
circumstances. This image is taken on an integration time of 100 ms. (Bottom 
right) A 300 |iim of thickness and a 1500 |iim from the midline of depth slide's 
image, showing the false color of the CA3 Hippocampus region under 405 nm 
and 3.5 mW laser source illumination, being applied for 3 minutes of time. The 
image shows a real tissue damage which is caused by the laser source under 
these circumstances. This image is taken on an integration time of 100 ms 



30 



Now that, tissue damage was checked. Therefore, it was concluded that it needs to 
illuminate the section with much higher light intensities and exposure times to cause 
damage than what has been used during this study measurements. 



31 



CHAPTER III 



DATA ANALYSES, THE MODIFIED BEER-LAMBERT LAW, 
BRAIN ATLAS ESTABLISHMENT, AND RESULTS 

Data Analyses 

The results associated with this study are strictly taken from the following brain 
areas: MNTB, VNTB, LSO, PPT, SC, CAS, and Cerebellum. Although the images have 
been stored, yet they are still considered to be raw data and it is required to make it 
through a series of data analysis steps before they can be scientifically illustrated 
corresponding to multi-data presentations that serve to answer the fundamental questions 
and aims of this study. 

The results could be introduced by following these steps: the pre-stored images in 
a specific folder are reloaded to another viewer program that is programmed in Lab VIEW 
software as well, that allows retrieving the intensities from those images according to a 
cursor location that is also adjustable by the analyzer. Then, these intensities that are 
corresponding to each tissue thickness will be saved in an appropriate format. This 
process still be pursued by a sorting one and thereby, they are ready to be depicted now. 
A snap shot for the viewer program is illustrated in figure III.l. 



32 



E Tissue Light ScutterinB Viewer.iri Front Panel 




Figure III.l A snap shot for the viewer program front panel screen that is used for 
retrieving the intensities from the images and plotting them as a function of 
tissue thickness according to the specific cursor location 



Two programs that have been used in order to graph the resultant data are: 
MATLAB R2010a and Igor 6. That resulted curves are normalized so that they are in a 
comparable forms. It is of fundamental importance that these data are being fitted with 
the most suitable equation form to make it possible to extract some valuable parameters 
like the one mentioned sooner- the effective attenuation coefficient (/Uf) that belongs to 
each region under investigation. The first equation that had been used to fit the data was 



33 



the modified Beer-Lambert law for light scattering and absorption in biological tissues, 
which has the form of: 

I(x) = loe-i'tx 

In which: 

I(,x): is the optical power intensity as a function of tissue thickness (mW/mm^) 
/„: is the initial optical power intensity (mW/mm^) (when x=0 mm) 
[it: is the effective attenuation coefficient (1/mm) 
x: is the tissue thickness (mm) 

More elaborate theoretical background pertaining to the modified Beer-Lambert 
law is presented in the following section. 

Some of the results that had adopted this approach are shown in the figures III.4-6 
using MATLAB. In these figures, the "one" and "two" words refer to the first and second 
measurements on the first and second slices used in that experiment, respectively. A full 
comprehensive description for the experiment that the following figures have been based 
on is elucidated as follows: 

In this experiment, a 600 \im thick slice is used and punched through different 
depth following the multiple different step-sizes of the motor (5 i^m step-size are used). 
The total moving distance was 500 |.im in depth making the smallest thickness taking into 
our consideration to be 100 |.im. The optical source used in this experiment is a blue LED 
light (453 nm) coupled to a 100 |^m core diameter optical fiber with an output power of 
4.33 mW/mm from this fiber. The LED source is driven by a 28 mA current to get this 
power. The CCD camera was set on 50 ms exposure time throughout the experiment. 



34 



The aims of these data analyses are to extract the pixels' digital intensities from 
the images taken. Then, get rid of the saturation values. After that, the raw data are drawn 
and their exponential curves are obtained. These raw data and fitting curves are 
normalized, as well, in order to make the results comparable to each other properly. 



Digital Intensity (Normali:ed) Versus Tissue's Tliicl<ness (urn) 




Figure III.2 A cerebellum one raw data and fitting curve. Note the offset in the fit. 
This issue will be addressed below 



35 



Digital Intensity [Nomallzed] Versus Tissue's Thickness [urn] 




Tissue's Thickness (uni) 



Figure III.3 A comparison between PPT one and PPT two. Note the offset in the fit. 
This issue will be addressed below 




Figure III.4 A comparison between CA3 one and CA3 two. Note the offset in the fit. 
This issue will be addressed below 



36 



The obtained data follows an exponentially decaying curve as predicted by the 
modified Beer- Lambert law. However, due to the electronic offset and other optical 
background, there is an artificial offset needed to be accounted in the data. Having taken 
that into account, the new fitting equation, for now, looks like the following: 

/(x) = +/oe-^*t^ 

One can simply see that this equation is of the same format as the old one with 
only one term added to it which is Fq which refers to that initial intensity. Thus, the same 
data reanalyzed applying the latter approach and this time using Igor programming, and 
the results are demonstrated in the following figures (Figure III.5 and Figure III.6). It is 
also important to indicate that "Tau" in these figures accounts for the effective attenuation 
coefficients. 




!i Kmu 

lstgtoteT3u=«.9ei (1*niir) 
2rel9i:)teTau=«6.7()2(i;tr[r) 



4 I I i ' » I — L. 



1 i I ■ T [ 

: m WD sa m 

Figure III.5 A comparison between PPT one and PPT two after taking the offset 
factor Yg into account which demonstrates its significant impact on the 
reanalyzed and refitted the data 

37 



as l5t globe la(j=19.M(3i'iiiin| 
CM2nilglobeTaj=eai73 (tfmm) 




Figure III.6 A comparison between CA3 one and CA3 two after taking the offset 
factor Yg into account which demonstrates its significant impact on the 
reanalyzed and refitted the data 



The Modified Beer-Lambert Law and the Effective Attenuation Coefficients for 

Highly Scattering Neural Targets 

The full mathematical treatment of light travelling in biological tissue that absorbs 
and scatters light-waves (or optical photons) is described by the Radiative Transport 
Equation (RTE) [13], [14]. 
1 dlif,s,t) 



■ + 



s ■ VL(F, s,t)+{jj^+ iJ^ )l(F, 5, - p f " L(F, s, t)p{s'-s)dn' =S(7,s,t) 

JO 



c dt 

Where L{f,s,t) is the radiance (W mT^sr'^') of the propagating light-wave; pL^ 
and Hg are the absorption, scattering coefficients (m~^) of the biological tissue; P{s'-s) 



38 



is the phase function describing the probability of a photon scattered to the radiation 
direction s' from its original radiation direction s; S(r,s,t) is the optical energy density 

(W m~^sr~^) generated in the biological tissue; c is the speed of light in vacuum and 0. 
is the solid angle. 



depends on both the spatial coordinate ( r ) and the radiation direction (s) and time (t). 



computationally with the RTE but requires an involved computational algorithm such as 
a Monte-Carlo stochastic simulation [15], [16]. Therefore, to extract quantitative 
parameters from our empirical measurements, a simplification of the RTE is needed. For 
most biological samples, including the brain, the scattering coefficient at the wavelengths 
tested here is typically one to two orders of magnitude higher than the absorption 
coefficient (jUj » ju^). In addition, the phase function P[s'-s) can be approximated by the 
Heyney-Greenstein function [17]: 



Where g is the anisotropy factor and is generally assumed to be larger than ~0.9 
(0.9 < ^ < 1) in most biological tissues, indicating that the scattering light is 
predominantly forward-scattered. Under these conditions, the RTE can be approximated 
by the diffusion equation (the details of the simplification can be found in [13]: 



The RTE is a complex equation which has no analytical solution, since 




resulting in a function with seven independent variables. L{r,s,t) can be evaluated 




1 dl(7,t) 
c 8t 



1 



W^I(j,t) = S(j,t) 



39 



Am 

Where /(r,0 = ^L{r,s,t)dQ. is the irradiance (W m~^), or in the laboratory 



commonly (but erroneously) called intensity of the light wave, and 

4a- 

S(r,t) = 4^^S(r,s,t)dD. . To further simply the diffusion equation, we further assume 



that the optical propagation is in a steady-state condition ( dl(r, t)/dt = 0) and there is no 
light being generated in the biological tissue S(r,t) = 0. Therefore, the ID diffusion 
equation can simply be written as a ID second-order differential equation [14]: 

Where ^gff = ^j^l^a^l^a + A^s(l ~ 5)] is the effective attenuation coefficient. 
Hence, the solution of the ID diffusion equation is the modified Beer-Lambert Law [14]: 

I(z) 

—— = T{z)^exp{-MeffZ) 

With Ig being the irradiance measured at the fiber output of the optical fiber, and 
z being the longitudinal distance from the fiber output. The ratio of /(z) against Ig is the 
optical transmittance r(z) which follows an exponential decay against the longitudinal 
distance z. In this study, we attempt to estimate the optical penetration depth within a 
brain nucleus to determine optical fiber source excitation efficacy of the opsin expressed 
within this neural target. It is clear from the above equation that it is not necessary -at the 
three wavelengths tested hereto individually measure fXa, l^s 9- Rather, simply 
measuring the effective attenuation coefficient /^e// is sufficient for this estimation. 



40 



The Brain Atlas, and a Technique of Mapping the Effective Attenuation Coefficients 

across the Entire Brain 

The technique of using an optical fiber to punch through a brain slice allows 
collecting data from well identified brain areas at very precise depths. However, it would 
be impractical to use this technique to map the effective attenuation coefficients /u^ (f) 

of many (i.e. hundreds) of brain areas, which would be required to obtain a quantitative 
picture across the entire brain. However, imaging brain slices using bright-field light 
transmission microscopy with monochromatic light and combining these images with the 
measured effective attenuation coefficients obtained from the punch-through method on 
selected neural targets allowed us to calculate and map out the effective attenuation 
coefficients across the entire brain. Whole brain slice imaging was performed on an 
Olympus VS 120 microscope, using transmitted light filtered via 546 /20 nm band-pass 
filter and a lOx (N.A. 0.40) objective. To allow seamless, quantitatively correct tiling of 
multiple images of a single brain section, the manufacturer calibrated the microscope to 
normalize for uniform illumination and data acquisition across the entire imaging area. 
With this normalization, the illumination irradiance 1^ can be assumed to be a constant 
across the whole brain slice scan. 

The illumination irradiance Iq of the microscope is difficult to measure directly, 
instead brain slices containing the brain areas measured previously with the punch- 
through method were used to quantify and normalize Iq. For a previously measured brain 
area, using the modified Beer-Lambert law, the illumination irradiance Iq can be 
estimated by 



41 



Effective attenuation coefficients iJ-effix, y) of other brain areas not measured 
with the punch-through method can subsequently be calculated using 

1 I(,x,y,Zo) 
f^effix,y) = - — loge[ ] 

The Effective Excitation Distance for Optogenetic Proteins 

In optogenetic experiments, it is important to estimate the minimum optical 
irradiance required to effectively excite the desired neural area longitudinally to 
maximize excitation of the optogenetic proteins. Assuming the minimum excitation 
irradiance threshold for an optogenetic protein is and the irradiance at the fiber 
output is Ifibev the effective excitation distance d in the longitudinal direction of a neural 
target, which has an effective attenuation coefficient of /^g// can be calculated by the 
following equation 

1 / • 
d = -- — loge[7 ] 

H-eff ifiber 

Integration of All Relevant Data in a Computer Program 

From a practical point of view, an investigator wishing to perform optogenetic 
manipulations in-vivo in the brain area of his/her choice needs to be able to estimate the 
required light intensity that needs to be fed into an optical fiber to obtain optimal 
illumination of the brain area to be manipulated. A situation where too much light energy 
is used may result in tissue damage and is therefore undesirable. Furthermore, feeding too 
much light energy into an optical fiber may result in unspecific activation of optogenetic 

42 



proteins outside the intended brain area, potentially compromising the experimental 
design. On the other hand, in a situation where not enough light energy is used, 
optogenetic proteins will fail to be activated. To aid with determining the correct amount 
of hght energy for a given experimental situation, we prepared a brain atlas that maps 
effective attenuation coefficients across the entire mouse brain. This atlas is integrated 
into a computer program that an investigator may use to estimate the required amount of 
light energy for an individual experimental situation based on brain area, desired 
penetration depth, and light frequency used. For further information, see 
www.optogeneticsapp.com . 

Results 

The main goal of this study was to test the hypothesis that different brain neural 
targets scatter light differently, and that these differences are significantly large such that 
they need to be considered for successful optogenetic activation in deep brain nuclei. A 
secondary goal was to establish a database of light scattering values for different regions 
of the mouse brain that could be used as a reference in future experiments in which 
illumination of neural tissue is required. The most common approach to bring light into 
deep brain areas invivo is via optical fibers that are stereotactically placed above the brain 
area of interest. Our experimental approach of advancing a light emitting optical fiber 
through brain tissue modeled such a situation well, and enabled us to precisely determine 
hght intensity at any depth along the longitudinal axis with respect to the fiber tip. 



43 



Light Intensity Decreases Exponentially in Brain Tissue 

An acute brain slice was placed into a perfusion chamber under an inverted 
microscope, and an optical fiber attached to a LED was placed directly on the tissue 
surface. Light emitted from this fiber propagated through the slice and was then collected 
by the objective and the chip of the attached monochromatic camera. A sketch of this 
configuration is shown in figure 11.21, and an example of an original image acquired with 
this setup is shown in figure n.23. This configuration of imaging the light emitted from 
an optical fiber tip after it passed through a piece of brain tissue of known origin and of a 
known thickness d allowed effective measurement of the remaining light intensity at 
tissue depth d. From this value we could then calculate the ratio of the intensity of 
remaining light at depth d over the original light intensity at the optical fiber tip. 

Subsequently, the optical fiber was lowered into the section in 5 |xm steps, and 
similar images were acquired with each step. Control experiments verified that advancing 
the fiber into the tissue caused it to reliably slice through the section rather than compress 
the section (data not shown). Advancing the fiber into the tissue (referred to as the "fiber 
punch-through method"), and taking repeated images at various depths effectively 
created a dataset of light intensity measurements in brain tissue at points progressively 
closer to the fiber tip. An alternative approach would have been to cut brain slices of 
different thicknesses and measuring light transmitted through each one of these slices. 
However, the fiber punch-through method allowed us to control for tissue depth 
(thickness) much more precisely than cutting sections of various thicknesses would have 
allowed us to do, and furthermore allowed us to measure the exact same piece of tissue at 
different depths. 

44 



From the measurements obtained at various tissue depths, light intensity ratios 
were calculated and plotted. Curve fitting indicated that the data points were best 
described by a single exponential function. An example of such a fit is shown in figure 
11.24, representing a set of measurements with blue light (453 nm) recorded from a 
section of PPT. The '+' symbols represent the measured luminance at each tissue 
thickness, and the superimposed line represents the exponential fit. 



Light Scattering Properties Vary across Different Brain Regions 

Eight different brain regions were measured with 453 nm light in the same way as 
the PPT shown before (Figure in.7). The data points (colored symbols) were plotted 
against the distance from the fiber tip, and the set of measurements from each brain area 
were fitted with a single exponential function (colored lines). 



o 


MNTB 




VNTB 




LSO 


<J 


PPT 




SC 





CA3 


o 


Cerebellum 




OB 




50 



100 150 200 

Tissue Thickness (|jm) 



250 



300 



Figure III.7 Optical transmittance through different types of brain tissue. 

Measurements using the fiber punch-through technique were taken in eight 
different brain areas with blue (453 nm) light. In each case, optical 
transmittance decreased exponentially with tissue thickness; however, the 
exponential decreases observed varied greatly with the type of tissue. Single 
measurements are represented by the respective symbols while the solid lines 
represent exponential fits of the data 



45 



The results indicate that light intensity dropped at least 10-fold within a 200 
distance from the tip of the optical fiber in each brain region tested. Importantly, the data 
suggest that this drop differs substantially among the brain regions tested. To 
systematically examine these differences, we calculated scattering coefficients from the 
data (Figure III.8). Average coefficients ranged from 19.96 +/- 0.26 for VNTB tissue, 
representing the lowest light transmittance of any region tested, to 9.76 +/- 0.78 for 
cerebellum, representing the highest transparency of all brain regions tested. For all 
values and SEMs, see figure III. 8 and corresponding figure caption. 




Brain Area 



Figure III.8 Effective attenuation coefficients with SEMs for the eight brain areas: 
VNTB 19.96 +/- 0.26 (1/mm); CA3 19.12 +/- 0.84 (1/mm); MNTB 18.16 +/- 0.69 
(1/mm); LSO 17.92 +/- 0.80 (1/mm); PPT 15.26 +/- 0.78 (1/mm); OB 14.88 +/- 
0.74 (1/mm); SC 13.91 +/- 0.83 (1/mm); CerebeUum 9.76 +/- 0.78 (1/mm) 



The MNTB, VNTB and LSO were measured with three wavelengths of light, 
while all other nuclei were measured with one wavelength, (see table III.l for summary). 
One set of measurements was performed per brain nucleus per hemisphere. 



46 



Table III.l Brain areas that were measured with three different wavelengths, and 
sample size (the unit of the effective attenuation coefficient is 1/mm) [12] 



Brain Area. 


Effective Attenuation Coefficient ^eff (l/mm) 


Kl— 'IDJ (^niTi) 






iVlIN lis 


lo.io ^n=iij 


id.oO (,n=vj 


i^.oO (,n=oj 


VIM lis 


ly.Vo (,n=o; 


17. ov (n=7 ) 


14. (n=7 ) 


T CO 


1 / \ \\ — ^ ) 


1 c 01 (x\—n\ 




PPT 


15.26 (n=10) 






sc 


13.91 (n=10) 






CAS 


19.12 (n=8) 






Cerebellum 


9.76 (n=8) 






Olfactory 


14.88 (n=5) 







Figures 111.9 and figure III. 10 show the practical consequences of these 
differential coefficients on light penetration through the different tj^es of tissue. Figure 
III. 9 plots the optical power required to illuminate neurons up to a tissue depth of 300 |xm 
below the optical fiber tip with a light intensity of at least 10 mW/mm (the light power 
required for ChR2 activation 8-12mW/mm^ [3]). To achieve this goal in cerebellar cortex, 
about 1.5 mW need to be emitted from the tip of the optical fiber, while in the case of 
VNTB, about 20 times as much optical power is required to achieve the same goal. 



47 




Brain Area 

Figure III.9 Optical power values that would need to be fed into a 100 diameter 
optical fiber when 300 \im of tissue needs to be illuminated at intensities typically 
used for Channelrhodopsin activation 

Due to the nonlinear nature of light distribution in tissue, these differences 
become more dramatic for deeper penetration. For example, doubling the illumination 
depth from 300 \xm to 600 |j,m would require about 20x the light intensity in the case of 
cerebellar cortex tissue (28 mW). By contrast, illuminating 600 |j,m of VNTB tissue to the 
same degree would require 12 W of light intensity, or 400 times the intensity required to 
illuminate 300 |j,m (Figure III. 10). 



48 




Brain Area 



Figure III.IO Same as figure III.ll except that in this example the illumination was 
calculated to hypothetically activate Channelrhodopsin over a distance of 600 
(im from the fiber tip 

These calculations suggest substantial differences in light scattering among 
different brain areas, and make the point that certain manipulations are possible in some 
brain areas but not others. 

Light Scattering Varies with Wavelength 

A travehng wave interferes with objects that are larger than its wavelength, but 
tends to bend around objects smaller than its wavelength. Thus, long wavelength light 
penetrates tissue deeper than short wavelength light. Since different lightsensitive 
molecules are optimally excited at a variety of wavelengths, we tested the influence of 
hght wavelength on the penetration depth of light in brain tissue. Figure III. 1 1 represents 
experiments in which MNTB was tested with three wavelengths: 453 nm, 528 nm, and 
940 nm. As expected, the longest wavelength (940 nm) showed the most effective 
penetration, i.e. the smallest attenuation of light intensity with increasing distance from 

49 



the fiber tip (red line), while the blue light (453 nm) attenuated within the shortest 
distance from the fiber tip (blue line). 




Figure III.llEffects of wavelength on optical transmittance. Optical transmittance 
in the MNTB as a function of tissue thickness and optical wavelengths. The three 
colorcoded data sets represent corresponding measurements with light of three 
different optical wavelengths (blue (453 nm), green (528 nm), and red (940 nm)). 
Longer-wavelength light penetrates tissue deeper, resulting in a higher 
transmittance at any given tissue thickness [12] 

Similar observations were made for a second brain area (VNTB) that was tested 
in the same way (Figure III. 12). 



50 




Tissue Thickness (|jm) 

Figure III.12 Optical transmittance in the VNTB as a function of tissue thickness 
and optical wavelengths. The three colorcoded data sets represent corresponding 
measurements with light of three different optical wavelengths (blue (453 nm), 
green (528 nm), and red (940 nm)). Longer-wavelength light penetrates tissue 
deeper, resulting in a higher transmittance at any given tissue thickness 

Note that optical absorption cannot be neglected at all light frequencies (an 
assumption made for the three single light frequencies tested in this study), and thus there 
is no simple linear extrapolation between the points shown in figure III. 13 [18]. 



51 



LU 



12^ 
400 



O MNTB 
□ VNTB 



500 



600 700 

Wavelength (nm) 



800 



900 



1000 



Figure III.13 Effects of light wavelength on transmittance in two brain areas 
(MNTB and VNTB). The effective attenuation coefficient decreases with 
wavelength for the three wavelengths tested. MNTB measurements are 
represented by round symbols while VNTB measurements are represented by 
square symbols. Measurements in the three different colors are indicated by the 
color-code of the symbols [12] 

While the datapoints can be fitted with a single exponential (Figure III. 14), the 



relationship may be more complex [18]. 




400 500 600 700 800 900 1000 

Wavelength (nm) 



Figure III.14 MNTB and VNTB proposed fitting curves for the effective attenuation 
coefficients as a function of wavelengths 



52 



Light Scattering Brain Atlas 

While the fiber punch-through method allowed for measurements of light 
scattering properties in anatomically defined brain areas, it is a relatively slow method. 
Measuring many different brain areas with this technique would not be feasible. 
However, to extend usage of our data to other areas of the brain without the need for 
additional punch-through measurements, we prepared a brain atlas containing light 
scattering values from the entire mouse brain. For this atlas, sections of 300 iim thickness 
were prepared from mouse brains, and imaged with an Olympus virtual microscopy 
system (Olympus VS 120) using monochromatic transmitted light (546 nm band pass 
filtered with a 20 nm band-pass width). The resulting images consist of relative 
differences in tissue translucency in grey scale between different brain areas in the 
section. Figure 111.15 shows an example of such an image, with several nuclei marked 
with colored lines on the section. 



53 



Figure III.15 Relating fiber punch-though measurements to brain atlas 

measurements. An image of a 300 ^m coronal section of mouse brain stem, taken 
on a calibrated virtual microscopy system with monochromatic light. Areas with 
higher optical transmittance appear brighter on the image, while areas with 
lower transmittance appear darker. MNTB, VNTB, and LSO are outlined in 
red, orange, and yellow, respectively [12] 

For brain areas that were also measured with the punch-though method, the 
relative grey values of the images correlated very well with the effective attenuation 
coefficients measured with the punch-through method (Figure III. 16), suggesting that the 
grey values of the images can be used as a basis to calculate the effective attenuation 
coefficients for brain areas that have not been tested with the punchthrough method. 



54 




0.2 0.4 0.6 0.8 1.0 

Normalized digital irradiance from Olympus images 

Figure III.16 Correlation in digital irradiance for brain areas tested with both the 
fiber punch-through and the virtual microscopy method. Digital irradiance was 
measured in six brain areas (MNTB (red), VNTB (orange), LSO (yellow), PPT 
(green), SC (light blue), and cerebellum (dark blue) with both the fiber punch 
through and the virtual microscopy technique. Results were normalized and 
plotted against each other. Each colored symbols represents the measurements 
from one brain area with two methods, the solid line indicates complete overlap 
between the measurements. The bars attached to each data point represent the 
standard error [12] 



55 



Importantly, the grey value images in combination with the effective attenuation 
coefficients measured with the punch-through method allowed us to establish an atlas of 
brain translucency that can be used to calculate the light scattering properties of any brain 
area in the adult mouse brain. 

Applying the Data to Experimental Design 

An investigator planning an experiment involving light activation of a given 
protein in-vivo is typically interested in the amount of light required to activate the 
protein at a distance d, from the fiber tip. In order to correctly determine the required 
amount of light, the following parameters must be considered: 1) The wavelength of the 
hght, 2) the largest distance from the fiber tip at which proteins are to be activated, 3) the 
specific light scattering properties of the brain area involved, and 4) the diameter of the 
fiber tip. We produced a computer program that calculates the required amount of light 
for a given experiment based on user input of these parameters. Screenshots from this 
computer program can be seen in the following figures. The program also incorporates 
the brain atlas described above. For further information, see www.optogeneticsapp.com . 



56 



Optogenetics 



Fiber Optical Power 



From 


1 mW 


> 


To 

- 


100 mW 


> 


Fiber Core Diameter 


100 urn 




> 


Optogenetic Protein 


ChR2 




> 

> 

* 


Protein Activation Percentage 


50% 




> 


Neural Target 


Target at Brain Atlas 




> 

> 




Plot 




> 




Figure III.19 The desired input parameters control panel 



57 




Figure III.20 The attainable penetration depth as a function of optical power at the 
fiber tip for the desired entered input parameters 



58 





20:33 




Image No : 12 









This version does not contain a full brain atlas. 
For complete brain atlas, please see Optogeniics Pro, the full version of this APP. 




^^^^^ 

4 





V 




Plate 12/43 

approjtimately Bregma +1 .0 mm 



Popnejror Limited 
www.popnejron.com 









— ^ 

Pafamater Ertry 




Uanusl 



Figure III.21 A sample image from the brain atlas where the investigator can select 
the area of interest precisely such that its optical properties are designated, and 
the corresponding penetration depth and optical power at the fiber tip are 
calculated, accordingly 

59 



iPad •1=^ 



20:40 



96% B 



Optogenetics 
Version 2.2 
User Manual 



Overview: 

Optogenetics is a tool that aids an investigator in calculating the required optical power for a given j'n-vfvo 
experiment involving optogenetics or any other experimental approach that includes light delivery to deep brain 
areas via optical fibers. To estimate the amount of light required for a given experimental design, knowledge about 
the specific scattering properties of the brain region of choice, the specific opsin to be used, and the properties of the 
optical fiber are required. A user enters these parameters into the APP, which then calculates the light scattering for 
the specific experimental situation. The APP includes a full brain atlas for the adult mouse brain (Pro Version), from 
which a user can look up the specific scattering properties of the brain area of choice. All data and all computations 
that are used in this APP are published in: Al-Juboori, Dondzillo, Stubblefield, Felseii, Lei, and Klug: Light 
scattering properties vary across different regions of the adult mouse brain. PlosONE, in press. 
For more information, pis see vrww. optogenetic sapp, com , 

Parameter Entry Screen: 



CIV1 1 ' 



The Paramettii' Entrj: screen has six data entry fields into which the desired experimental parameters can be entered, 
either via drop-down menus, or via the keyboard. 

The six parameters are: 

Fiber Optical Power: 

Enter the minimum and inaxirauin optical power you wish to use, or that your equipment is able to produce. The 
penetration depth plot (see below) will plot the maximum penetration depth for each power value between the 
miminum and raaxinium power values set here. 



Fibei'core diameter: 






o 






Psremeter Erhy 


Brain Alias 


Manual 



Figure III.22 A screenshot for tlie user manual tiiat is available in the computer 
program also, in which the user can be taken through details about how to use 
this application to its full extent 



60 



CHAPTER IV 



DISCUSSION AND MAIN FINDINGS 
Discussion 

This study has been dealing with a lot of cardinal questions about the best 
approach that these measurements must be conducted in order to make its main tasks 
achievable. It has also been tackling many technical and practical issues; however, these 
problems have eventually been overcome by modifications for the system setup. 

So far this study has shown that it could be a necessity to choose different 
illumination profiles and sources to activate some brain areas maybe through various 
light profiles or side emitting fibers. . .etc. It has also been acknowledged that the regions 
under study can be arranged from the densest to the least optically dense as VNTB, CA3, 
MNTB, LSO, PPT, OB, SC,and Cerebellum, respectively, as illustrated in figure in.8. 

Another crucial aspect that this study has explored is the optical properties age 
dependence for those brain tissues within the same species. Moreover, it has also shown 
how important the tissue health is and how it affects the measurements all in all, and how 
the time degradation rate for those brain tissues play a major role in their optical 
characteristics. Most importantly, it shed light on the situation when there is a 
photosensitive florescent material within the same region that is highly likely to emit 
light back after being shining with a certain wavelength which gives awkwardly incorrect 
results. And definitely this phenomenon should be avoided or resolved somehow. 

On the flip side, there are still few "on stage" complexities that should be 
mitigated. One of which is the camera saturation when it comes to very thin sample 

61 



thickness and that decreases the number of points that are taken for curves construction 
and narrow the total moving distance, and eventually, it becomes obscure for the fitting 
program to establish the best fitting approach. Another problem that has happened 
sometimes is what so-called, humorously, "the pillow effect". Simply, it's the same 
response that a pillow might respond when it is pushed from the middle and that will be 
lifting its sides up higher. Applying this on a sample with one of the threads or strings in 
the middle will lead to the same results and might alter the readings severely, sometimes. 

Yet, altogether, this study is still promising, especially, for the methodology of 
doing it this way that has not been done widely. 

Main Findings 

There are four main findings of this study: 1) Light emitted into brain tissue from 
a point source such as an optical fiber declines exponentially in intensity with increasing 
distance from the fiber tip 2) There are substantial differences in light scattering 
properties among different brain neural areas, resulting in a need for specific knowledge 
about any given brain area to be illuminated 3) The light wavelength used in a particular 
experiment additionally influences the scattering properties, with longer wavelength light 
penetrating deeper into the tissue 4) The results obtained in this study could be integrated 
into a brain atlas of Ught scattering in the mouse brain, as well as a computer program 
that allows a user to easily determine the light requirements for any given experimental 
situation. 

The most important finding is the observation that there are substantial 

differences in the optical properties across different brain areas. For simplicity, previous 

studies have assumed that light propagation through brain tissue is similar throughout the 

62 



brain, and have calculated the light requirements for optogenetic experiments with a 
single effective attenuation coefficient [1], [10], [1 1]. Our results show that a differential 
approach is needed, because the observed differences in effective attenuation coefficients 
can have substantial consequences on experimental design. Figure III.9 and figure III. 10 
illustrates this point and suggest that certain manipulations are possible in some brain 
areas but not others. 

In some experiments, one might want to restrict the volume of illumination, e.g. if 
an opsin is widely expressed in the brain [19] but only a certain region is to be 
manipulated with light. Thus, specific knowledge of the light requirements for a given 
experimental situation can inform an optimal experimental design, and this includes 
knowledge about the specific light attenuation properties of the brain area to be 
manipulated, as well as knowledge about how different light wavelengths will affect the 
illumination. 



63 



CHAPTER V 



IMPROVEMENTS, COMPARISON WITH PREVIOUS STUDIES, 

AND FUTURE PLANS 

Improvements 

A handful of improvements that would shift the accuracy and performance to the 
edge are being thought seriously to be incorporated at this stage of doing this research 
toward perfecting a three-dimensional (3D) light attenuation model for the brain. One of 
these enhancements is to find out a more positive way to tell whether the fiber tip is right 
at the top of sample surface neither far away from it, nor punched through it. Another 
interesting scheme to measure would be obtainable by inserting some mechanical 
properties that the sample could be described with to resolve the mystery behind the 
actual act that is happening while the optical fiber is punching through, for instance; is it 
punching through smoothly, pushing it to other sides through a random process, or 
tearing the sample (which might be one of the reasons why there has been CCD camera 
intensity saturations happening at some points when the fiber tip gets closer to the bottom 
of the chamber). Hopefully, that will lead to an optomechanical three-dimensional (3D) 
model for the light being attenuated in those brain areas. 

Another empirical idea that has been come up with, recently, is what it could be 
established by some minor adjustments to the system setup by changing the optical 
intensities for the optical fibers that will be traversing a specific sample thickness through 
tuning the current intensity. That allows erecting, at least, two handy graphs for each 
sample thickness associated with a certain optical fiber manufacturer specifications and 

64 



the wavelength used. One of them would be the actual initial optical power intensity 
measured at the sample surface as a function of current intensity- for a specific laboratory 
experimental setup. The other one is the optical power intensity measured after the light 
makes it through the whole sample thickness as a function of the initial one that has been 
started with. Having done that, it will provide actual real numerical values for the optical 
intensities needed to be delivered to carry out the desired action with the corresponding 
initial ones that they should be started with in hand for the targeted brain area embedded 
under certain depth. The results of this experiment could be incorporated with and used 
for further examination, solidification, and confirmation to the results of this study. 

Comparison with Previous Studies 

Aravanis and colleagues [1] first characterized the optical scattering effect in 
mouse brain cortical tissue by measuring the optical attenuation at different slice 
thicknesses. In their work, the Kubelka-Munk model (7 = 1/(5 ■ z + 1) where 5 is the 
scattering coefficient) was used in their data fitting. However, our measurements were 
best fitted with an exponential function and the data cannot be satisfactory fitted with the 
KubeUca-Munk equation. The discrepancy mainly occurs at larger distances (z > 
200 //m), and our data show that light attenuates much faster than predicted by the 
KubeUca-Munk model, resulting in a much reduced excitation distance of neural targets in 
our results. A comparison between the two different fitting equations on a PPT raw data 
is shown in figure V.l. 



65 




0.0 



+ PPT Raw Data 

— Our Exponential Fit 

— Kubelka-Munk Fit 







50 



100 



150 

Tissue Thickness {|jm) 



200 



250 



300 



Figure V.l A comparison between our exponential fit and Kubelka-Munk fit for a 
PPT raw data showing that it is best fitted with a single exponential curve 

More recently, Stark et al. [20] report that their measurements of optical attenuation 
at larger distances from the fiber tip cannot be well fitted with the Kubelka-Munk 
equation, although at shorter distances the data fit with the equation is good. The 
differences are likely due to the different optical detectors being used in these 
experiments. In our measurements, a single pixel of the CCD camera along the center of 
the propagation axis of the optical fiber was used to construct the optical transmittance 
curve. By contrast, the previous studies used a large area photodetector to measure the 
optical attenuation, which also collects light not strictly propagating along the optical 
axis. This difference could potentially result in differences in the data. Having taken that 
into account, total intensity measurements were calculated and averaged over the entire 
detector's area, and the results still indicate that the data can not be well fitted with the 
Kubelka-Munk equation but rather a single exponential curve as shown in figure V.2. 



66 




100 200 300 400 500 

Tissue Thickness {|jm) 



Figure V.2 A comparison between our exponential fit and Kubelka-Munk fit for an 
MNTB total intensity measurements of the raw data averaged over the entire 
detector's area showing that it is best fitted with a single exponential curve 

When light comes out of an optical fiber tip, light spread as well as the radius of 
light increases as light propagates further away from the fiber output. This cone shape of 
hght propagation increases the beam area (^4), thus reducing the optical irradiance of the 
light beam (/ = P / A). However, this reduction of optical irradiance due to beam 
spreading from the optical fiber is much more gradual than the optical scattering in the 
brain tissue, so this beam spreading effect can be neglected or considered to be absorbed 
in the effective attenuation coefficient /Ue//- For example, the numerical aperture (NA) of 
the 100 urn core (r = 50 pmi) diameter optical fiber that was used in Our measurement is 
0.22, such that the acceptance angle of the light cone is 9.5 degree {NA = 
n sirC^ 6 where n — 1.33 in water). The radius of the beam increases over a 
propagation distance of d = 500 iim by 83 fim {5r = d tan 0); thus the beam area 
increases by a factor of 7, resulting in an optical irradiance reduction to 14% of its 

67 



original output. At the same time, according to our measurements, the optical 
transmittance of the MNTB due to optical scattering after 500 nm of propagation is 
0.01% at 453nm wavelength. Therefore, we conclude that the optical fiber beam 
spreading is not a significant effect in estimating the optical irradiance in brain tissues. 

Future Plans 

Application of the Findings to Future Experiments 

One goal of this study was to provide a body of knowledge on light scattering 
properties of the mouse brain that could be used by investigators as a tool to optimize the 
light stimulation for a specific experimental situation. To this end, data from several brain 
areas were collected but the fiber punch-through method, while allowing us to obtain data 
in great detail, was not efficient enough to use for a multitude of brain areas. Therefore 
we resorted to virtual microscopy to image the entire mouse brain with monochromatic 
transmitted light. The resulting images consisted of gray-value pixels, which represented 
the differences in optical properties between these different brain areas. The differences 
in grey values between different brain areas obtained with virtual microscopy 
corresponded well with the differences observed in the fiber punch-through method, 
allowing us to calibrate the results from the two approaches to each other. Thus, we 
obtained data on the light scattering properties of the entire mouse brain, allowing an 
investigator to look up the brain area of choice in the light scattering atlas, and 
determining the associated specific effective attenuation coefficient for that area. This 
coefficient can be entered into a computer program, together with information on the 
desired stimulation wavelength and volume of brain tissue to be illuminated super- 

68 



threshold. The computer program then estimates the required light intensity at the optical 
fiber tip to meet the desired criteria. The use of these tools should allow an experimenter 
to design optogenetic manipulation in-vivo with better precision and more confidence that 
the brain area to be activated by light will actually be illuminated at a super-threshold 
intensity. Moreover, the delivered light can be adjusted to be super-threshold for opsin 
activation in the desired brain area, and fall to sub-threshold values at the borders of the 
brain area of interest, reducing unspecific activation of adjacent neuronal areas. For 
further information, see www.optogeneticsapp.com . 

Research Proposal for Determining Diffusivity Constants for Individual Brain 
Areas 

While the concept of using Optogenetics is growing tremendously and becoming 
more involved in a variety of research and development studies in the field of 
neuroscience and some other relevant branches which could be: robotics and neural 
networks and fuzzy control soft computing (maybe in the future), there are still a handful 
of related parameters to this methodology that require more investigation and some of 
which are still undetermined. For example, the optical, mechanical, and thermal 
properties of different brain areas. The knowledge about those parameters is of 
significant importance to achieve the desired activation or stimulation for those targeted 
brain areas precisely, accurately, and without damaging the brain tissues. In this 
experiment we are interested in determining the conductivity or diffusivity constants for 
individual brain areas. This will introduce the idea of delivering above the threshold 
amount of optical power intensity assumed to activate the neurons from cortex, without 
having the optical fiber punch through them; using a pulsed laser with specific 

69 



parameters. For instant, the pulse energy, the pulse duration or the pulse width, and the 
Pulse Repetition Rate (PRR)- that match those conductivity or diffusivity constants under 
study. Having done that, the heat accumulation and the consequent brain tissue damage 
that is expected to happen via using Continuous Wave (CW) lasers of high-power will be 
compensated for. If the threshold optical power intensity for a targeted area, the effective 
attenuation coefficient due to scattering and absorption phenomena per unit length, and 
the conductivity or diffusivity constant (unit power per unit length per unit time; i.e. 
(mW mm s ) were known, and after a few calculations, all it is needed to do is to 
match the time required for that pulse to reach a certain depth with PRR for the laser. In 
that case, the energy will be transferred to the targeted spot, and at the same time, get rid 
of the excessive energy that will be building up if the laser source was functioning in a 
CW mode; through the diffusing process of that energy during the off -mode between 
pulses. In order to carry out this experiment, a sample from the area under investigation 
will be labeled by two different tj^es of fluorophores: Midori-Ishi Cyan (MiCy)- one of 
the Cyan Fluorescent Proteins (CFP)s, and mRFPl- one of the Red Fluorescent Proteins 
(RFP)s. Those two Fluorophores have the properties shown in table V.l. 



70 



Table V.l Midori-Ishi Cyan and mRFPl properties [21] 



Fluorophore 
Type 


Excitation 
Maximum 
(nm) 


Emission 

Maximum 

(nm) 


Molar 

Extinction 

Coefficient 


Quantum 
Yield 


In vivo 
Structure 


Relative 
Brightness 
(% of 
EGFP) 


Midori-Ishi 

Cyan 

(MiCy) 


472 


495 


27,300 


0.90 


Dimer 


73 


mRFPl 


584 


607 


50,000 


0.25 


Monomer 


37 



In addition to that, their excitation and emission spectra are illustrated in figure 



V.3 and figure V.4. 



MiCy and mKO Fluorescent Protein FRET Pair Spectral Profiles 




36D 400 4S0 GOO £50 GOO 650 

Wavelength {Nanometers) 



Figure V.3 MiCy excitation and emission spectra [22] 



71 




Wavelength (nm) 



Figure V.4 mRFPl absorption (solid line), excitation (dotted line), and emission 
(dashed line) spectra [23] 

Those probes are suitable for conducting this experiment for their excitation peaks 
pretty close to the activation maxima for Channelrhodopsin-2 (ChR2) which is 
approximately 470 nm and Halorhodopsin (NpHR) which is approximately 580 nm [9]; 
where ChR2 and NpHR are the fundamental constituents of any Optogenetics study. 
Their activation spectra are depicted in figure V.5. 




325 425 525 625 725 
Wavelength (nm) 

Figure V.5 ChR2 and NpHR activation spectra [4] 



72 



From light sources perspectives, this experiment can be operated with one of the 
EPL series of Picosecond (ps) Pulsed Diode Lasers; like the ones from Edinburgh 
Instruments with a wavelength of 470 nm and featuring 10 set repetition frequencies from 
20 kHz to 20 MHz and pulse widths down to ca. 70 ps [24]. Whereas, the 580 nm 
wavelength could be obtained from an Nd:YAG laser (1064 nm) after a frequency 
doubling process followed by Q-switching operation to get the desired pulse shape [25]. 
These light sources will be attached and coupled to optical fibers, and some of their 
specifications such as: energy, both duration or width, and PRR would be highly 
preferred to be adjustable and tunable. Moreover, some wavelength selection filters could 
be used, as well, to improve and optimize the system experimental set-up and 
performance. 



73 



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